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Granular base equivalency

From Wikipedia, the free encyclopedia
Measure of road pavement thickness
Profile of pavement showing the different layers of material in a certain road in Ontario. The thickness of these layers can be translated to GBE.

Granular base equivalency orgranular base equivalence (GBE) is a measure of totalpavement thickness.[1][2] Since pavement is composed of multiple layers with different physical properties, its total thickness is measured by GBE. GBE translates the thickness of different road layers to a number using a set of coefficients. So, to calculate the GBE, the depth of each layer should be multiplied by the granular equivalency factor for the material in that layer. In the next step the sum of the converted layer thicknesses is calculated.[2] This sum is calledgranular base equivalency, which is a popular and important measure in pavement design andpavement performance modeling.[3][4][5]

Example

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Here is an example of GBE calculation adopted from Piryonesi (2019).[1] This example belongs to a road in theLTPP database. This road is made of the following layers: subbase, base, and three layers of hot mixed asphalt concrete. Their thicknesses are given in millimeters in the following table. The total GBE for this road 805.7 millimeters.

LayerThickness (mm)Conversion coefficientEquivalent thickness or GBE (mm)
Hot mixed asphalt30.5261.0
Hot mixed asphalt58.52117.0
Hot mixed asphalt38.1276.2
Base144.81144.8
Subbase607.10.67406.7
Total--805.7

References

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  1. ^abPiryonesi, Sayed Madeh (November 2019).Piryonesi, S. M. (2019). The Application of Data Analytics to Asset Management: Deterioration and Climate Change Adaptation in Ontario Roads (Doctoral dissertation) (Thesis).
  2. ^abHaas, R., and Kazmierowski, T. 1996. TAC's New Management Design and Management Guide. Transportation Association of Canada (TAC), Ottawa.
  3. ^Piryonesi, S. M.; El-Diraby, T. E. (2020) [Published online: December 21, 2019]. "Data Analytics in Asset Management: Cost-Effective Prediction of the Pavement Condition Index".Journal of Infrastructure Systems.26 (1).doi:10.1061/(ASCE)IS.1943-555X.0000512.S2CID 213782055.
  4. ^Piryonesi S. Madeh; El-Diraby Tamer E. (2020-06-01)."Role of Data Analytics in Infrastructure Asset Management: Overcoming Data Size and Quality Problems".Journal of Transportation Engineering, Part B: Pavements.146 (2): 04020022.doi:10.1061/JPEODX.0000175.S2CID 216485629.
  5. ^"Public Works Canada (1992). "Manual of Pavement Structural Design," Public Works Canada, Architectural and Engineering Services, Air Transportation"(PDF).
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